Download PacktPub | Apache Spark 3 for Data Engineering and Analytics with Python [Video] [FCO] torrent - GloDLS
Login
Nome de Usuário:
senha:
Remember Me:
[Cadastre-se]
[Recuperar conta]
Latest Forums Topics
Friends
Hack Storm
Friendly Site

FTU Apps
Friendly site

Get Into Way
Friendly site

KaranPC
Friendly site

OneHack
Friendly site

IGGGames
Friendly site

Detalhes do Torrent Para "PacktPub | Apache Spark 3 for Data Engineering and Analytics with Python [Video] [FCO..."

PacktPub | Apache Spark 3 for Data Engineering and Analytics with Python [Video] [FCO...

To download this torrent, you need a BitTorrent client: Vuze or BTGuard
baixar esse torrent
Download using Magnet Link

Saúde:
Sementes: 85
Leechers: 20
Concluído: 1,174 
Última verificado: 01-01-2022 19:27:50

pontos Uploader Reputação : 19810





Write a Review for the Uploader:   245   Say Thanks with one good review:
Share on Facebook
Details
Nome:PacktPub | Apache Spark 3 for Data Engineering and Analytics with Python [Video] [FCO...
Description:




By: David Mngadi
Released: August 2021
Course Source: https://www.packtpub.com/product/apache-spark-3-for-data-engineering-and-analytics-with-python-video/9781803244303

Video Details

ISBN 9781803244303
Course Length 8 hours 30 minutes

About

Apache Spark 3 is an open-source distributed engine for querying and processing data. This course will provide you with a detailed understanding of PySpark and its stack. This course is carefully developed and designed to guide you through the process of data analytics using Python Spark. The author uses an interactive approach in explaining keys concepts of PySpark such as the Spark architecture, Spark execution, transformations and actions using the structured API, and much more. You will be able to leverage the power of Python, Java, and SQL and put it to use in the Spark ecosystem.

You will start by getting a firm understanding of the Apache Spark architecture and how to set up a Python environment for Spark. Followed by the techniques for collecting, cleaning, and visualizing data by creating dashboards in Databricks. You will learn how to use SQL to interact with DataFrames. The author provides an in-depth review of RDDs and contrasts them with DataFrames.

There are multiple problem challenges provided at intervals in the course so that you get a firm grasp of the concepts taught in the course.

The code bundle for this course is available here: https://github.com/PacktPublishing/Apache-Spark-3-for-Data-Engineering-and-Analytics-with-Python-

Author

David Mngadi

David is a data management professional who is influenced by the power of data in our lives and has helped several companies become more data-driven to gain a competitive edge as well as meet the regulatory requirements. In the last 15 years, he has had the pleasure of designing and implementing data warehousing solutions in retail, telco, and banking industries, and recently in more big data lake-specific implementations. He is passionate about technology and teaching programming online.

Video YouTube:
Categoria:Tutorials
Idioma:English  English
Total Size:2.16 GB
Informações Hash:25D04B48387A14D6D1036EA5C872F8E04B040091
Adicionado por:Prom3th3uS Super AdministratorMovie PirateVIP
Data adicionada:2021-09-17 06:16:46
Torrent Status:Torrent Verified


Ratings:Not Yet Rated (Log in to rate it)


Tracker:
udp://tracker.torrent.eu.org:451/announce

Este Torrent também tem trackers de backup
URLSemeadoresLeechersConcluído
udp://tracker.torrent.eu.org:451/announce000
udp://tracker.tiny-vps.com:6969/announce000
http://tracker.foreverpirates.co:80/announce830
udp://tracker.cyberia.is:6969/announce000
udp://exodus.desync.com:6969/announce10287
udp://explodie.org:6969/announce710
udp://tracker.opentrackr.org:1337/announce112749
udp://9.rarbg.to:2780/announce8245
udp://tracker.internetwarriors.net:1337/announce9234
udp://ipv4.tracker.harry.lu:80/announce000
udp://open.stealth.si:80/announce9246
udp://9.rarbg.to:2900/announce8245
udp://9.rarbg.me:2720/announce8245
udp://opentor.org:2710/announce72123


Lista de arquivos: 





Comments
Nenhum comentário postado ainda